Refereed Papers

Paper Title:
Effort Estimation: How Valuable is it for a Web company to Use a Cross-company Data Set, Compared to Using Its Own Single-company Data Set?

Authors:

Emilia Mendes (The University of Auckland)

Sergio Di Martino (University of Salerno)

Filomena Ferrucci (University of Salerno)

Carmine Gravino (University of Salerno)

Abstract:
Previous studies comparing the prediction accuracy of effort models built using Web cross- and single-company data sets have been inconclusive, and as such replicated studies are necessary to determine under what circumstances a company can place reliance on a cross-company effort model.
This paper therefore replicates a previous study by investigating how successful a cross-company effort model is: i) to estimate effort for Web projects that belong to a single company and were not used to build the cross-company model; ii) compared to a single-company effort model. Our single-company data set had data on 15 Web projects from a single company and our cross-company data set had data on 68 Web projects from 25 different companies. The effort estimates used in our analysis were obtained by means of two effort estimation techniques, namely forward stepwise regression and case-based reasoning.
Our results were similar to those from the replicated study, showing that predictions based on the single-company model were significantly more accurate than those based on the cross-company model.